Neue Suche
Prof. Dr. Thomas Bartz-Beielstein
Kontaktdaten
E-Mail:
thomas.bartz-beielstein@th-koeln.de
Webseite:
Publikationen:
Als Projektleitung
Projektmitglied
- Entwicklung zuverlässiger KI-basierter virtueller Sensoren für Kraftfahrzeuge, mit Fokus auf Genauigkeit und Robustheit; Bartz-Beielstein Thomas; Bundesministerium für Bildung und Forschung
- European ECS industry sovereignty and manufacturing independence through perfecting programmable ECS for automobiles; Bartz-Beielstein Thomas; Key Digital Technologies Joint Undertaking
- TH Köln - Künstliche Intelligenz^plus (Anteil TBB / AR); Bartz-Beielstein Thomas; Bundesministerium für Bildung und Forschung
Projektmitglied
Als Autor*in:
Als Herausgeber*in
- Multi-Objective Optimization and Hyperparameter Tuning With Desirability Functions
- Tuning for Trustworthiness
- An Experimental Comparison of Batch and Online Machine Learning Algorithms
- A Novel Ranking Scheme for the Performance Analysis of Stochastic Optimization Algorithms Using the Principles of Severity
- Bed-Attached Vibration Sensor System: A Machine Learning Approach for Fall Detection in Nursing Homes
- Besondere Anforderungen an OML-Verfahren
- Besondere Anforderungen an OML-Verfahren
- Drift Detection and Handling
- Drifterkennung und -behandlung
- Drifterkennung und –behandlung
- Ein experimenteller Vergleich von Batch- und Online Machine Learning-Algorithmen
- Ein experimenteller Vergleich von Batch- und Online-Machine-Learning-Algorithmen
- Einleitung
- Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution
- Evaluation and Performance Measurement
- Evaluation und Performance-Messung
- Evaluation und Performanzmessung
- Hyperparameter Tuning
- Hyperparameter Tuning
- Hyperparameter-Tuning
- Initiale Auswahl und nachträgliche Aktualisierung von OML Modellen
- Initiale Auswahl und nachträgliche Aktualisierung von OML-Modellen
- Initial Selection and Subsequent Updating of OML Models
- Introduction
- Open-Source Software for Online Machine Learning
- Open-Source-Software für Online Machine Learning
- Open-Source-Software für Online Machine Learning
- Practical Applications of Online Machine Learning
- Praxisanwendungen
- Praxisanwendungen
- Simplifying Hyperparameter Tuning in Online Machine Learning
- Special Requirements for Online Machine Learning Methods
- Summary and Outlook
- Supervised Learning
- Supervised Learning
- Supervised Learning
- Zusammenfassung und Ausblick
- Zusammenfassung und Ausblick
- A Robust Statistical Framework for the Analysis of the Performances of Stochastic Optimization Algorithms Using the Principles of Severity
- Cognitive Architecture for Artificial Intelligence
- Hyperparameter Tuning Cookbook
- Konviviale Künstliche Intelligenz
- Online Machine Learning and Surrogate-Model-Based Optimization for Improved Production Processes Using a Cognitive Architecture
- PyTorch Hyperparameter Tuning – A Tutorial for SpotPython
- Benchmark-Driven Configuration of a Parallel Model-Based Optimization Algorithm
- Case Study I: Tuning Random Forest (Ranger)
- Case Study II
- Case Study III: Tuning of Deep Neural Networks
- Co-Optimizing for Task Performance and Energy Efficiency in Evolvable Robots
- Elevator Group Control as a Constrained Multiobjective Optimization Problem
- Global Study
- Hyperparameter Tuning and Optimization Applications
- Hyperparameter Tuning Approaches
- Models
- Ranking and Result Aggregation
- Tuning
- Bayesian Networks for Mood Prediction Using Unobtrusive Ecological Momentary Assessments
- Behavior-Based Neuroevolutionary Training in Reinforcement Learning
- Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems
- Experimental Investigation and Evaluation of Model-Based Hyperparameter Optimization
- Impact of Energy Efficiency on the Morphology and Behaviour of Evolved Robots
- Optimization and Adaptation of a Resource Planning Tool for Hospitals Under Special Consideration of the COVID-19 Pandemic
- Resource Planning for Hospitals Under Special Consideration of the COVID-19 Pandemic
- Resource Planning for Hospitals under Special Consideration of the COVID-19 Pandemic: Optimization and Sensitivity Analysis
- Stochastic Satellite Tracking with Constrained Budget via Structured-Chromosome Genetic Algorithms
- Tuning Algorithms for Stochastic Black-Box Optimization
- Underwater Acoustic Networks for Security Risk Assessment in PublicDrinking Water Reservoirs
- A New Taxonomy of Global Optimization Algorithms
- Architektur und Transport: Seillose, lineare Aufzüge und Künstliche Intelligenz
- Benchmarking in Optimization
- Benchmarking in Optimization
- CAAI
- CAAI - A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems
- CAAI - A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems
- Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems
- Einsatz künstlicher Intelligenz in der Bedarfsplanung im Gesundheitswesen, hier in der Bedarfsplanung von Intensivbetten im Pandemiefall
- EventDetectR – An Open-Source Event Detection System
- EventDetectR-An Open-Source Event Detection System
- Expected Improvement versus Predicted Value in Surrogate-Based Optimization
- Expected Improvement versus Predicted Value in Surrogate-Based Optimization
- Expected Improvement versus Predicted Value in Surrogate-Based Optimization
- Feature Selection for Surrogate Model-Based Optimization
- High-Lift Devices Topology Optimisation using Structured-Chromosome Genetic Algorithm
- Hospital Capacity Planning Using Discrete Event Simulation Under Special Consideration of the COVID-19 Pandemic
- Hybrid Variable Selection and Support Vector Regression for Gas Sensor Optimization
- Improving the Reliability of Test Functions Generators
- Optimization of High-dimensional Simulation Models Using Synthetic Data
- Parallelized Bayesian Optimization for Expensive Robot Controller Evolution
- Parallelized Bayesian Optimization for Problems with Expensive Evaluation Functions
- Preliminary Spacecraft Design by Means of Structured-Chromosome Genetic Algorithms
- Sensor Placement for Contamination Detection in Water Distribution Systems
- Sensor Placement for Contamination Detection in Water Distribution Systems
- Sequential Parameter Optimization for Mixed-Discrete Problems
- Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools
- Technical Report: Flushing Strategies in Drinking Water Systems
- Technical Report: Flushing Strategies in Drinking Water Systems
- Understanding the Behavior of Reinforcement Learning Agents
- Variable Reduction for Surrogate-Based Optimization
- Variable Reduction for Surrogate-Based Optimization
- An Empirical Approach for Probing the Definiteness of Kernels
- Autonomous Generation of Observation Schedules for Tracking Satellites with Structured-Chromosome GA Optimisation
- Evaluation of Cognitive Architectures for Cyber-Physical Production Systems
- Evaluation of Cognitive Architectures for Cyber-Physical Production Systems
- Feature Selection for Surrogate Model-Based Optimization
- Improving NeuroEvolution Efficiency by Surrogate Model-based Optimization with Phenotypic Distance Kernels
- Improving NeuroEvolution Efficiency by Surrogate Model-Based Optimization with Phenotypic Distance Kernels
- Open Issues in Surrogate-Assisted Optimization
- Structured-chromosome GA Optimisation for Satellite Tracking
- Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning
- Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning
- Variablenreduktion für Surrogat-Modell basierte Optimierung
- Weighted Ensembles in Model-Based Global Optimization
- Why We Need an AI-Resilient Society
- An Empirical Approach for Probing the Definiteness of Kernels
- An Empirical Approach For Probing the Definiteness of Kernels
- A new Taxonomy of Continuous Global Optimization Algorithms
- A New Taxonomy of Continuous Global Optimization Algorithms
- Comparison of Parallel Surrogate-Assisted Optimization Approaches
- Comparison of Parallel Surrogate-Assisted Optimization Approaches
- Distance-based Kernels for Surrogate Model-based Neuroevolution
- Expensive Optimisation Exemplified by ECG Simulator Parameter Tuning
- Global Optimization Strategies
- Linear Combination of Distance Measures for Surrogate Models in Genetic Programming
- Linear Combination of Distance Measures for Surrogate Models in Genetic Programming
- Model-Based Evolutionary Algorithm for Optimization of Gas Distribution Systems in Power Plant Electrostatic Precipitators
- Modellgestützter Evolutionärer Algorithmus zur Optimierung von Gasverteilsystemen in Elektroabscheidern von Kohlekraftwerken
- Modelling Zero-inflated Rainfall Data through the Use of Gaussian Process and Bayesian Regression
- Optimization via Multimodel Simulation
- Optimization via Multimodel Simulation
- Potential Complex Optimisation Problems in Science and Industry
- Surrogate Assisted Optimization of Particle Reinforced Metal Matrix Composites
- Bias-Correction of Satellite Rainfall Estimates Through the Use of Metamodels using Gaussian Process and Bayesian Regression.
- Can Social Learning Increase Learning Speed, Performance or Both?
- Conditional Inference Trees for Knowledge Extraction from Motor Health Condition Data
- Conditional Inference Trees for the Knowledge Extraction from Motor Health Condition Data
- imputeTS
- In a Nutshell
- In a Nutshell -- The Sequential Parameter Optimization Toolbox
- Is Social Learning More than Parameter Tuning?
- Meta-Model Based Optimization of Hot Rolling Processes in the Metal Industry
- Model-based Methods for Continuous and Discrete Global Optimization
- Modeling and Calibration of Robust Gas Sensors
- Simulation-based Test Functions for Optimization Algorithms
- Simulation-based Test Functions for Optimization Algorithms
- Structural Health Monitoring for Resource
- Structural Health Monitoring von Faserverbundstrukturen mittels Piezosensoren
- Surrogate Assisted Learning of Neural Networks
- Surrogate-Assisted Learning of Neural Networks
- Trinkwassersicherheit mit Predictive Analytics und Oracle
- Trinkwassersicherheit mit Predictive Analytics und Oracle
- Trinkwasser-Sicherheit mit Predictive Analytics und Oracle
- A Survey of Model-based Methods for Global Optimization
- Building Ensembles of Surrogate Models by Optimal Convex Combination (Preprint)
- Building Ensembles of Surrogates by Optimal Convex Combination
- Data Processing
- EASD-experimental Algorithmics for Streaming Data
- Efficient Global Optimization with Indefinite Kernels
- Experimental Algorithmics Applied to On-line Machine Learning
- Forschendes Lernen - vom Bachelor zur Promotion in den Ingenieurswissenschaften
- Forschendes Lernen - vom Bachelor zur Promotion in den Ingenieurswissenschaften
- Forschendes Lernen – vom Bachelor zur Promotion in den Ingenieurwissenschaften
- From Real World Data to Test Functions
- Metamodel-based Optimization of Hot Rolling Processes in the Metal Industry
- Model-based Methods for Continuous and Discrete Global Optimization
- Modeling and Optimization of a Robust Gas Sensor
- Modeling and Optimization of a Robust Gas Sensor
- Multi-fidelity Modeling and Optimization of Biogas Plants
- Optimization of the Cyclone Separator Geometry via Multimodel Simulation
- Stacked Generalization of Surrogate Models - A Practical Approach
- Tutorials at PPSN 2016
- Analyzing Capabilities of Latin Hypercube Designs Compared to Classical Experimental Design Methods
- CIMO - CI-basierte Mehrkriterielle Optimierungsverfahren für Anwendungen in der Industrie
- Comparison of different Methods for Univariate Time Series Imputation in R
- How to Create Generalizable Results
- Learning Model-Ensemble Policies with Genetic Programming
- MCIOP - Mehrkriterielle CI-basierte Optimierungsverfahren für den industriellen Einsatz
- Meaningful Problem Instances and Generalizable Results
- Overview: Evolutionary Algorithms
- Sequential Parameter Optimization in Noisy Environments
- Uncertainty Management Using Sequential Parameter Optimization
- Boosting Parameter-Tuning Efficiency with Adaptive Experimental Designs
- Distance Measures for Permutations in Combinatorial Efficient Global Optimization
- Does Imputation Work for Improvement of Domestic Hot Water Usage Prediction?
- Efficient Global Optimization for Combinatorial Problems
- Evolutionary Algorithms
- Multi-fidelity Modeling and Optimization of Biogas Plants
- Tuning Multi-Objective Optimization Algorithms for Cyclone Dust Separators
- A Case Study on Multi-Criteria Optimization of an Event Detection Software under Limited Budgets
- A Framework for the Empirical Analysis of Genetic Programming System Performance
- A Gentle Introduction to Multi-Criteria Optimization with SPOT
- Comparing Ensemble-Based Forecasting Methods for Smart-Metering Data
- FIWA - Methoden der Computational Intelligence für Vorhersagemodelle in der Finanz-und Wasserwirtschaft (Schlussbericht)
- How to Create Meaningful and Generalizable Results
- Simulation and Optimization of Cyclone Dust Separators
- Simulation and Optimization of Cyclone Dust Separators
- UniFIeD Univariate Frequency-Based Imputation for Time Series Data
- A Gentle Introduction to Sequential Parameter Optimization
- Beyond Particular Problem Instances
- Editorial for the Special Issue on Automated Design and Assessment of Heuristic Search Methods
- Ensemble-Based Model Selection for Smart Metering Data
- Mehrkriterielle sequentielle Parameteroptimierung für Anwendungs-Probleme mit stark limitiertem Budget
- Model-Assisted Multi-Criteria Tuning of an Event Detection Software under Limited Budgets
- Multi-Criteria Optimization for Hard Problems under Limited Budgets
- Sequential Parameter Optimization for Symbolic Regression
- SPOT Applied to Non-Stochastic Optimization Problems
- Statistical Analysis of Optimization Algorithms With R
- Tuning and Evolution of Support Vector Kernels
- Automatic and Interactive Tuning of Algorithms
- Ensemble Based Optimization and Tuning Algorithms
- Noisy Optimization with Sequential Parameter Optimization and Optimal Computational Budget Allocation
- Tuned Data Mining
- Tuned Data Mining in R
- Clustering Based Niching for Genetic Programming in the R Environment
- Comparing SPO-Tuned GP and NARX Prediction Models for Stormwater Tank Fill Level Prediction
- Introduction
- Optimization of Biogas Production with Computational Intelligence a Comparative Study
- Optimization of Support Vector Regression Models for Stormwater Prediction
- Parameter-Tuned Data Mining
- RGP
- Sequential Model-Based Parameter Optimisation
- SPOT
- SPOT: A Toolbox for Interactive and Automatic Tuning in the R Environment
- The Future of Experimental Research
- The Sequential Parameter Optimization Toolbox
- Tuning and Experimental Analysis in Evolutionary Computation
- Optimierte Modellierung von Füllständen in Regenüberlaufbecken mittels CI-basierter ParameterselektionOptimized Modelling of Fill Levels in Stormwater Tanks Using CI-based Parameter Selection Schemes
- Reinforcement Learning for Games
- The Future of Experimental Research
- Experimental Research in Evolutionary Computation
- How Experimental Algorithmics Can Benefit from Mayo’s Extensions to Neyman–Pearson Theory of Testing
- Parameterselektion für komplexe Modellierungsaufgaben der Wasserwirtschaft
- Reinforcement Learning
- Experimental Research in Evolutionary Computation
- Multi-Objective Evolutionary Design of Mold Temperature Control Using DACE for Parameter Optimization
- Particle Swarm Optimization and Sequential Sampling in Noisy Environments
- Sequential Parameter Optimization Applied to Self-Adaptation for Binary-Coded Evolutionary Algorithms
- Experimental Research in Evolutionary Computation
- High-Order Punishment and the Evolution of Cooperation
- Investigation of One-Go Evolution Strategy/Quasi-Newton Hybridizations
- Optimizing Door Assignment in LTL-Terminals by Evolutionary Multiobjective Algorithms
- SPOT–-A Toolbox for Visionary Ideas
- The Impact of Group Reputation in Multiagent Environments
- Evolution Strategies and Threshold Selection
- Sequential Parameter Optimization
- Validation and Optimization of an Elevator Simulation Model with Modern Search Heuristics
- Design and Analysis of Optimization Algorithms Using Computational Statistics
- Systematic Analyses of Multi-Objective Evolutionary Algorithms Applied to Real-World Problems Using Statistical Design of Experiments
- Tuning Search Algorithms for Real-World Applications
- Optimal Elevator Group Control by Evolution Strategies
- Particle Swarm Optimizers for Pareto Optimization with Enhanced Archiving Techniques
- Circuit Design Using Evolutionary Algorithms
- Design of Evolutionary Algorithms and Applications in Surface Reconstruction
- Threshold Selection, Hypothesis Tests, and DOE Methods
- Thresholding-a Selection Operator for Noisy ES
- Informatik an einer Waldorfschule
- Evolutionary Algorithms for the Optimization of Simulation Models Using PVM
Als Herausgeber*in
- Online Machine Learning
- Online Machine Learning
- Online Machine Learning
- Hyperparameter Tuning for Machine and Deep Learning with R
- High-Performance Simulation-Based Optimization
- Proceedings of the 21st International Multiconference INFORMATION SOCIETY – IS 2018
- Parallel Problem Solving from Nature - PPSN XIII
- Experimental Methods for the Analysis of Optimization Algorithms
- Hybrid Metaheuristics
- Control of Traffic Systems in Buildings
- Festschrift Hans-Paul Schwefel 2006
Publikationsliste
Publikationsliste (CSV)
Publikationsliste (PDF) im "American Psychological Association 6th edition (DOI)"-Zitierstil
Publikationsliste (PDF) im "Anglia Ruskin University - Harvard"-Zitierstil
Publikationsliste (PDF) im "Gesellschaft für Bildung und Forschung in Europa - Harvard"-Zitierstil
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Projektleitung
Projektmitglied
- Entwicklung zuverlässiger KI-basierter virtueller Sensoren für Kraftfahrzeuge, mit Fokus auf Genauigkeit und Robustheit; Bartz-Beielstein Thomas; Bundesministerium für Bildung und Forschung
- European ECS industry sovereignty and manufacturing independence through perfecting programmable ECS for automobiles; Bartz-Beielstein Thomas; Key Digital Technologies Joint Undertaking
- TH Köln - Künstliche Intelligenz^plus (Anteil TBB / AR); Bartz-Beielstein Thomas; Bundesministerium für Bildung und Forschung
Projektmitglied
Als Autor*in::
- Multi-Objective Optimization and Hyperparameter Tuning With Desirability Functions
- Tuning for Trustworthiness
- An Experimental Comparison of Batch and Online Machine Learning Algorithms
- A Novel Ranking Scheme for the Performance Analysis of Stochastic Optimization Algorithms Using the Principles of Severity
- Bed-Attached Vibration Sensor System: A Machine Learning Approach for Fall Detection in Nursing Homes
- Besondere Anforderungen an OML-Verfahren
- Besondere Anforderungen an OML-Verfahren
- Drift Detection and Handling
- Drifterkennung und -behandlung
- Drifterkennung und –behandlung
- Ein experimenteller Vergleich von Batch- und Online Machine Learning-Algorithmen
- Ein experimenteller Vergleich von Batch- und Online-Machine-Learning-Algorithmen
- Einleitung
- Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution
- Evaluation and Performance Measurement
- Evaluation und Performance-Messung
- Evaluation und Performanzmessung
- Hyperparameter Tuning
- Hyperparameter Tuning
- Hyperparameter-Tuning
- Initiale Auswahl und nachträgliche Aktualisierung von OML Modellen
- Initiale Auswahl und nachträgliche Aktualisierung von OML-Modellen
- Initial Selection and Subsequent Updating of OML Models
- Introduction
- Open-Source Software for Online Machine Learning
- Open-Source-Software für Online Machine Learning
- Open-Source-Software für Online Machine Learning
- Practical Applications of Online Machine Learning
- Praxisanwendungen
- Praxisanwendungen
- Simplifying Hyperparameter Tuning in Online Machine Learning
- Special Requirements for Online Machine Learning Methods
- Summary and Outlook
- Supervised Learning
- Supervised Learning
- Supervised Learning
- Zusammenfassung und Ausblick
- Zusammenfassung und Ausblick
- A Robust Statistical Framework for the Analysis of the Performances of Stochastic Optimization Algorithms Using the Principles of Severity
- Cognitive Architecture for Artificial Intelligence
- Hyperparameter Tuning Cookbook
- Konviviale Künstliche Intelligenz
- Online Machine Learning and Surrogate-Model-Based Optimization for Improved Production Processes Using a Cognitive Architecture
- PyTorch Hyperparameter Tuning – A Tutorial for SpotPython
- Benchmark-Driven Configuration of a Parallel Model-Based Optimization Algorithm
- Case Study I: Tuning Random Forest (Ranger)
- Case Study II
- Case Study III: Tuning of Deep Neural Networks
- Co-Optimizing for Task Performance and Energy Efficiency in Evolvable Robots
- Elevator Group Control as a Constrained Multiobjective Optimization Problem
- Global Study
- Hyperparameter Tuning and Optimization Applications
- Hyperparameter Tuning Approaches
- Models
- Ranking and Result Aggregation
- Tuning
- Bayesian Networks for Mood Prediction Using Unobtrusive Ecological Momentary Assessments
- Behavior-Based Neuroevolutionary Training in Reinforcement Learning
- Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems
- Experimental Investigation and Evaluation of Model-Based Hyperparameter Optimization
- Impact of Energy Efficiency on the Morphology and Behaviour of Evolved Robots
- Optimization and Adaptation of a Resource Planning Tool for Hospitals Under Special Consideration of the COVID-19 Pandemic
- Resource Planning for Hospitals Under Special Consideration of the COVID-19 Pandemic
- Resource Planning for Hospitals under Special Consideration of the COVID-19 Pandemic: Optimization and Sensitivity Analysis
- Stochastic Satellite Tracking with Constrained Budget via Structured-Chromosome Genetic Algorithms
- Tuning Algorithms for Stochastic Black-Box Optimization
- Underwater Acoustic Networks for Security Risk Assessment in PublicDrinking Water Reservoirs
- A New Taxonomy of Global Optimization Algorithms
- Architektur und Transport: Seillose, lineare Aufzüge und Künstliche Intelligenz
- Benchmarking in Optimization
- Benchmarking in Optimization
- CAAI
- CAAI - A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems
- CAAI - A Cognitive Architecture to Introduce Artificial Intelligence in Cyber-Physical Production Systems
- Cognitive Capabilities for the CAAI in Cyber-Physical Production Systems
- Einsatz künstlicher Intelligenz in der Bedarfsplanung im Gesundheitswesen, hier in der Bedarfsplanung von Intensivbetten im Pandemiefall
- EventDetectR – An Open-Source Event Detection System
- EventDetectR-An Open-Source Event Detection System
- Expected Improvement versus Predicted Value in Surrogate-Based Optimization
- Expected Improvement versus Predicted Value in Surrogate-Based Optimization
- Expected Improvement versus Predicted Value in Surrogate-Based Optimization
- Feature Selection for Surrogate Model-Based Optimization
- High-Lift Devices Topology Optimisation using Structured-Chromosome Genetic Algorithm
- Hospital Capacity Planning Using Discrete Event Simulation Under Special Consideration of the COVID-19 Pandemic
- Hybrid Variable Selection and Support Vector Regression for Gas Sensor Optimization
- Improving the Reliability of Test Functions Generators
- Optimization of High-dimensional Simulation Models Using Synthetic Data
- Parallelized Bayesian Optimization for Expensive Robot Controller Evolution
- Parallelized Bayesian Optimization for Problems with Expensive Evaluation Functions
- Preliminary Spacecraft Design by Means of Structured-Chromosome Genetic Algorithms
- Sensor Placement for Contamination Detection in Water Distribution Systems
- Sensor Placement for Contamination Detection in Water Distribution Systems
- Sequential Parameter Optimization for Mixed-Discrete Problems
- Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools
- Technical Report: Flushing Strategies in Drinking Water Systems
- Technical Report: Flushing Strategies in Drinking Water Systems
- Understanding the Behavior of Reinforcement Learning Agents
- Variable Reduction for Surrogate-Based Optimization
- Variable Reduction for Surrogate-Based Optimization
- An Empirical Approach for Probing the Definiteness of Kernels
- Autonomous Generation of Observation Schedules for Tracking Satellites with Structured-Chromosome GA Optimisation
- Evaluation of Cognitive Architectures for Cyber-Physical Production Systems
- Evaluation of Cognitive Architectures for Cyber-Physical Production Systems
- Feature Selection for Surrogate Model-Based Optimization
- Improving NeuroEvolution Efficiency by Surrogate Model-based Optimization with Phenotypic Distance Kernels
- Improving NeuroEvolution Efficiency by Surrogate Model-Based Optimization with Phenotypic Distance Kernels
- Open Issues in Surrogate-Assisted Optimization
- Structured-chromosome GA Optimisation for Satellite Tracking
- Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning
- Surrogate Models for Enhancing the Efficiency of Neuroevolution in Reinforcement Learning
- Variablenreduktion für Surrogat-Modell basierte Optimierung
- Weighted Ensembles in Model-Based Global Optimization
- Why We Need an AI-Resilient Society
- An Empirical Approach for Probing the Definiteness of Kernels
- An Empirical Approach For Probing the Definiteness of Kernels
- A new Taxonomy of Continuous Global Optimization Algorithms
- A New Taxonomy of Continuous Global Optimization Algorithms
- Comparison of Parallel Surrogate-Assisted Optimization Approaches
- Comparison of Parallel Surrogate-Assisted Optimization Approaches
- Distance-based Kernels for Surrogate Model-based Neuroevolution
- Expensive Optimisation Exemplified by ECG Simulator Parameter Tuning
- Global Optimization Strategies
- Linear Combination of Distance Measures for Surrogate Models in Genetic Programming
- Linear Combination of Distance Measures for Surrogate Models in Genetic Programming
- Model-Based Evolutionary Algorithm for Optimization of Gas Distribution Systems in Power Plant Electrostatic Precipitators
- Modellgestützter Evolutionärer Algorithmus zur Optimierung von Gasverteilsystemen in Elektroabscheidern von Kohlekraftwerken
- Modelling Zero-inflated Rainfall Data through the Use of Gaussian Process and Bayesian Regression
- Optimization via Multimodel Simulation
- Optimization via Multimodel Simulation
- Potential Complex Optimisation Problems in Science and Industry
- Surrogate Assisted Optimization of Particle Reinforced Metal Matrix Composites
- Bias-Correction of Satellite Rainfall Estimates Through the Use of Metamodels using Gaussian Process and Bayesian Regression.
- Can Social Learning Increase Learning Speed, Performance or Both?
- Conditional Inference Trees for Knowledge Extraction from Motor Health Condition Data
- Conditional Inference Trees for the Knowledge Extraction from Motor Health Condition Data
- imputeTS
- In a Nutshell
- In a Nutshell -- The Sequential Parameter Optimization Toolbox
- Is Social Learning More than Parameter Tuning?
- Meta-Model Based Optimization of Hot Rolling Processes in the Metal Industry
- Model-based Methods for Continuous and Discrete Global Optimization
- Modeling and Calibration of Robust Gas Sensors
- Simulation-based Test Functions for Optimization Algorithms
- Simulation-based Test Functions for Optimization Algorithms
- Structural Health Monitoring for Resource
- Structural Health Monitoring von Faserverbundstrukturen mittels Piezosensoren
- Surrogate Assisted Learning of Neural Networks
- Surrogate-Assisted Learning of Neural Networks
- Trinkwassersicherheit mit Predictive Analytics und Oracle
- Trinkwassersicherheit mit Predictive Analytics und Oracle
- Trinkwasser-Sicherheit mit Predictive Analytics und Oracle
- A Survey of Model-based Methods for Global Optimization
- Building Ensembles of Surrogate Models by Optimal Convex Combination (Preprint)
- Building Ensembles of Surrogates by Optimal Convex Combination
- Data Processing
- EASD-experimental Algorithmics for Streaming Data
- Efficient Global Optimization with Indefinite Kernels
- Experimental Algorithmics Applied to On-line Machine Learning
- Forschendes Lernen - vom Bachelor zur Promotion in den Ingenieurswissenschaften
- Forschendes Lernen - vom Bachelor zur Promotion in den Ingenieurswissenschaften
- Forschendes Lernen – vom Bachelor zur Promotion in den Ingenieurwissenschaften
- From Real World Data to Test Functions
- Metamodel-based Optimization of Hot Rolling Processes in the Metal Industry
- Model-based Methods for Continuous and Discrete Global Optimization
- Modeling and Optimization of a Robust Gas Sensor
- Modeling and Optimization of a Robust Gas Sensor
- Multi-fidelity Modeling and Optimization of Biogas Plants
- Optimization of the Cyclone Separator Geometry via Multimodel Simulation
- Stacked Generalization of Surrogate Models - A Practical Approach
- Tutorials at PPSN 2016
- Analyzing Capabilities of Latin Hypercube Designs Compared to Classical Experimental Design Methods
- CIMO - CI-basierte Mehrkriterielle Optimierungsverfahren für Anwendungen in der Industrie
- Comparison of different Methods for Univariate Time Series Imputation in R
- How to Create Generalizable Results
- Learning Model-Ensemble Policies with Genetic Programming
- MCIOP - Mehrkriterielle CI-basierte Optimierungsverfahren für den industriellen Einsatz
- Meaningful Problem Instances and Generalizable Results
- Overview: Evolutionary Algorithms
- Sequential Parameter Optimization in Noisy Environments
- Uncertainty Management Using Sequential Parameter Optimization
- Boosting Parameter-Tuning Efficiency with Adaptive Experimental Designs
- Distance Measures for Permutations in Combinatorial Efficient Global Optimization
- Does Imputation Work for Improvement of Domestic Hot Water Usage Prediction?
- Efficient Global Optimization for Combinatorial Problems
- Evolutionary Algorithms
- Multi-fidelity Modeling and Optimization of Biogas Plants
- Tuning Multi-Objective Optimization Algorithms for Cyclone Dust Separators
- A Case Study on Multi-Criteria Optimization of an Event Detection Software under Limited Budgets
- A Framework for the Empirical Analysis of Genetic Programming System Performance
- A Gentle Introduction to Multi-Criteria Optimization with SPOT
- Comparing Ensemble-Based Forecasting Methods for Smart-Metering Data
- FIWA - Methoden der Computational Intelligence für Vorhersagemodelle in der Finanz-und Wasserwirtschaft (Schlussbericht)
- How to Create Meaningful and Generalizable Results
- Simulation and Optimization of Cyclone Dust Separators
- Simulation and Optimization of Cyclone Dust Separators
- UniFIeD Univariate Frequency-Based Imputation for Time Series Data
- A Gentle Introduction to Sequential Parameter Optimization
- Beyond Particular Problem Instances
- Editorial for the Special Issue on Automated Design and Assessment of Heuristic Search Methods
- Ensemble-Based Model Selection for Smart Metering Data
- Mehrkriterielle sequentielle Parameteroptimierung für Anwendungs-Probleme mit stark limitiertem Budget
- Model-Assisted Multi-Criteria Tuning of an Event Detection Software under Limited Budgets
- Multi-Criteria Optimization for Hard Problems under Limited Budgets
- Sequential Parameter Optimization for Symbolic Regression
- SPOT Applied to Non-Stochastic Optimization Problems
- Statistical Analysis of Optimization Algorithms With R
- Tuning and Evolution of Support Vector Kernels
- Automatic and Interactive Tuning of Algorithms
- Ensemble Based Optimization and Tuning Algorithms
- Noisy Optimization with Sequential Parameter Optimization and Optimal Computational Budget Allocation
- Tuned Data Mining
- Tuned Data Mining in R
- Clustering Based Niching for Genetic Programming in the R Environment
- Comparing SPO-Tuned GP and NARX Prediction Models for Stormwater Tank Fill Level Prediction
- Introduction
- Optimization of Biogas Production with Computational Intelligence a Comparative Study
- Optimization of Support Vector Regression Models for Stormwater Prediction
- Parameter-Tuned Data Mining
- RGP
- Sequential Model-Based Parameter Optimisation
- SPOT
- SPOT: A Toolbox for Interactive and Automatic Tuning in the R Environment
- The Future of Experimental Research
- The Sequential Parameter Optimization Toolbox
- Tuning and Experimental Analysis in Evolutionary Computation
- Optimierte Modellierung von Füllständen in Regenüberlaufbecken mittels CI-basierter ParameterselektionOptimized Modelling of Fill Levels in Stormwater Tanks Using CI-based Parameter Selection Schemes
- Reinforcement Learning for Games
- The Future of Experimental Research
- Experimental Research in Evolutionary Computation
- How Experimental Algorithmics Can Benefit from Mayo’s Extensions to Neyman–Pearson Theory of Testing
- Parameterselektion für komplexe Modellierungsaufgaben der Wasserwirtschaft
- Reinforcement Learning
- Experimental Research in Evolutionary Computation
- Multi-Objective Evolutionary Design of Mold Temperature Control Using DACE for Parameter Optimization
- Particle Swarm Optimization and Sequential Sampling in Noisy Environments
- Sequential Parameter Optimization Applied to Self-Adaptation for Binary-Coded Evolutionary Algorithms
- Experimental Research in Evolutionary Computation
- High-Order Punishment and the Evolution of Cooperation
- Investigation of One-Go Evolution Strategy/Quasi-Newton Hybridizations
- Optimizing Door Assignment in LTL-Terminals by Evolutionary Multiobjective Algorithms
- SPOT–-A Toolbox for Visionary Ideas
- The Impact of Group Reputation in Multiagent Environments
- Evolution Strategies and Threshold Selection
- Sequential Parameter Optimization
- Validation and Optimization of an Elevator Simulation Model with Modern Search Heuristics
- Design and Analysis of Optimization Algorithms Using Computational Statistics
- Systematic Analyses of Multi-Objective Evolutionary Algorithms Applied to Real-World Problems Using Statistical Design of Experiments
- Tuning Search Algorithms for Real-World Applications
- Optimal Elevator Group Control by Evolution Strategies
- Particle Swarm Optimizers for Pareto Optimization with Enhanced Archiving Techniques
- Circuit Design Using Evolutionary Algorithms
- Design of Evolutionary Algorithms and Applications in Surface Reconstruction
- Threshold Selection, Hypothesis Tests, and DOE Methods
- Thresholding-a Selection Operator for Noisy ES
- Informatik an einer Waldorfschule
- Evolutionary Algorithms for the Optimization of Simulation Models Using PVM
- Online Machine Learning
- Online Machine Learning
- Online Machine Learning
- Hyperparameter Tuning for Machine and Deep Learning with R
- High-Performance Simulation-Based Optimization
- Proceedings of the 21st International Multiconference INFORMATION SOCIETY – IS 2018
- Parallel Problem Solving from Nature - PPSN XIII
- Experimental Methods for the Analysis of Optimization Algorithms
- Hybrid Metaheuristics
- Control of Traffic Systems in Buildings
- Festschrift Hans-Paul Schwefel 2006
Publikationsliste
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Publikationsliste (PDF) im "American Psychological Association 6th edition (DOI)"-Zitierstil
Publikationsliste (PDF) im "Anglia Ruskin University - Harvard"-Zitierstil
Publikationsliste (PDF) im "Gesellschaft für Bildung und Forschung in Europa - Harvard"-Zitierstil
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